Designing a controller for autonomous vehicles capable of providing adequate performance
in all driving scenarios is challenging due to the highly complex environment and inability to …

Object detection, as of one the most fundamental and challenging problems in computer
vision, has received great attention in recent years. Over the past two decades, we have …

Human-centric perceptions (eg, pose estimation, human parsing, pedestrian detection,
person re-identification, etc.) play a key role in industrial applications of visual models. While …

Object detection generally requires sliding-window classifiers in tradition or anchor-based
predictions in modern deep learning approaches. However, either of these approaches …

Human detection has witnessed impressive progress in recent years. However, the
occlusion issue of detecting human in highly crowded environments is far from solved. To …

It is important to measure and analyze people behavior to design systems which interact
with people. This article describes a portable people behavior measurement system using a …

Pedestrian detection in a crowd is a very challenging issue. This paper addresses this
problem by a novel Non-Maximum Suppression (NMS) algorithm to better refine the …

Recent years have witnessed enormous progress in AI-related fields such as computer
vision, machine learning, and autonomous vehicles. As with any rapidly growing field, it …

Detecting small objects is notoriously challenging due to their low resolution and noisy
representation. Existing object detection pipelines usually detect small objects through …

Pedestrian detection in crowded scenes is a challenging problem since the pedestrians
often gather together and occlude each other. In this paper, we propose a new occlusion …